





'''simple docstring'''



from __future__ import annotations




def  _lowerCAmelCase    (					lowerCamelCase_      :	int		,							lowerCamelCase_      :	int					):
			if partitions <= 0:
						raise ValueError('''partitions must be a positive number!'''					)
			if partitions > number_of_bytes:
						raise ValueError('''partitions can not > number_of_bytes!'''					)
			__lowercase					    =				number_of_bytes // partitions
			__lowercase					    =				[]
			for i in range(UpperCamelCase_					):
						__lowercase					    =				i * bytes_per_partition + 1
						__lowercase					    =				(
						    number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
						)
						allocation_list.append(f"{start_bytes}-{end_bytes}"					)
			return allocation_list


if __name__ == "__main__":
	import doctest

	doctest.testmod()










'''simple docstring'''

import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE__     :						int	=  get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model''')

@require_sentencepiece
@require_tokenizers
class 							a__( snake_case__   ,      unittest.TestCase     ):
			a_	: List[Any]									=      GPTSwaTokenizer
			a_	: int									=      False
			a_	: List[Any]									=      True
			a_	: Any									=      False






			def 						_lowercase  (     self						)							->							str:
					super().setUp()

					# We have a SentencePiece fixture for testing
					snake_case__	     =GPTSwaTokenizer(_UpperCAmelCase					,   eos_token='<unk>'					,   bos_token='<unk>'					,   pad_token='<unk>'						)

					tokenizer.save_pretrained(self.tmpdirname						)






			def 						_lowercase  (     self					,   _UpperCAmelCase						)							->							Any:
					snake_case__	     ='This is a test'
					snake_case__	     ='This is a test'
					return input_text, output_text






			def 						_lowercase  (     self						)							->							str:
					snake_case__	     ='<s>'
					snake_case__	     =1

					self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCAmelCase						)					,   _UpperCAmelCase						)
					self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCAmelCase						)					,   _UpperCAmelCase						)






			def 						_lowercase  (     self						)							->							Optional[Any]:
					snake_case__	     =list(self.get_tokenizer().get_vocab().keys()						)

					self.assertEqual(vocab_keys[0]					,   '<unk>'						)
					self.assertEqual(vocab_keys[1]					,   '<s>'						)
					self.assertEqual(vocab_keys[-1]					,   'j'						)
					self.assertEqual(len(_UpperCAmelCase						)					,   2000						)






			def 						_lowercase  (     self						)							->							List[str]:
					self.assertEqual(self.get_tokenizer().vocab_size					,   2000						)






			def 						_lowercase  (     self						)							->							Any:
					snake_case__	     =GPTSwaTokenizer(_UpperCAmelCase						)

					snake_case__	     =tokenizer.tokenize('This is a test'						)
					self.assertListEqual(_UpperCAmelCase					,   ['▁This', '▁is', '▁a', '▁t', 'est']						)

					self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)					,   [465, 287, 265, 631, 842]						)

					snake_case__	     =tokenizer.tokenize('I was born in 92000, and this is falsé.'						)
					# fmt: off
					self.assertListEqual(
					    _UpperCAmelCase					,   ['▁I', '▁was', '▁bor', 'n', '▁in', '▁', '<0x39>', '2', '0', '0', '0', ',', '▁and', '▁this', '▁is', '▁f', 'al', 's', '<0xC3>', '<0xA9>', '.']					,   )
					# fmt: on

					snake_case__	     =tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)
					self.assertListEqual(
					    _UpperCAmelCase					,   [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]					,   )

					snake_case__	     =tokenizer.convert_ids_to_tokens(_UpperCAmelCase						)
					# fmt: off
					self.assertListEqual(
					    _UpperCAmelCase					,   ['▁I', '▁was', '▁bor', 'n', '▁in', '▁', '<0x39>', '2', '0', '0', '0', ',', '▁and', '▁this', '▁is', '▁f', 'al', 's', '<0xC3>', '<0xA9>', '.']						)
					# fmt: on






			def 						_lowercase  (     self						)							->							Optional[Any]:
					snake_case__	     =GPTSwaTokenizer(_UpperCAmelCase						)
					snake_case__	     =['This is a test', 'I was born in 92000, and this is falsé.']
					snake_case__	     =[
					    [465, 287, 265, 631, 842],
					    [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
					]

					# Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
					for text, expected_ids in zip(_UpperCAmelCase					,   _UpperCAmelCase						):
							self.assertListEqual(tokenizer.encode_fast(_UpperCAmelCase						)					,   _UpperCAmelCase						)

					# Test that decode_fast returns the input text
					for text, token_ids in zip(_UpperCAmelCase					,   _UpperCAmelCase						):
							self.assertEqual(tokenizer.decode_fast(_UpperCAmelCase						)					,   _UpperCAmelCase						)






			@slow
			def 						_lowercase  (     self						)							->							Dict:
					snake_case__	     =[
					    '<|python|>def fibonacci(n)\n    if n < 0:\n        print(\'Incorrect input\')',
					    'Hey there, how are you doing this fine day?',
					    'This is a text with a trailing spaces followed by a dot     .',
					    'Häj sväjs lillebrör! =)',
					    'Det är inget fel på Mr. Cool',
					]

					# fmt: off
					snake_case__	     ={'input_ids': [[6_3423, 5, 6811, 1_4954, 282, 816, 3821, 6_3466, 6_3425, 6_3462, 18, 6_3978, 678, 301, 1320, 6_3423, 6_3455, 6_3458, 18, 6_3982, 4246, 3940, 1901, 4_7789, 5547, 1_8994], [1_9630, 1100, 6_3446, 1342, 633, 544, 4488, 593, 5102, 2416, 6_3495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 5_8593, 2_2413, 9106, 546, 268, 3_3213, 6_3979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_5130, 6_3450, 924, 6_3449, 2249, 4062, 1558, 318, 6_3504, 2_1498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 6_3443, 2_6801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
					# fmt: on
					self.tokenizer_integration_test_util(
					    expected_encoding=_UpperCAmelCase					,   model_name='AI-Sweden/gpt-sw3-126m'					,   sequences=_UpperCAmelCase					,   )




